Abstract
Purpose - The purpose of this paper is to critically evaluate the state of the art of applications of organisational systematics and manufacturing cladistics in terms of strengths and weaknesses and introduce new generic cladistic and hierarchical classifications of discrete manufacturing systems. These classifications are the basis for a practical web-based expert system and diagnostic benchmarking tool. Design/methodology/approach - There were two stages for the research methods, with eight re-iterative steps: one for theory building, using secondary and observational data, producing conceptual classifications; the second stage for theory testing and theory development, using quantitative data from 153 companies and 510 manufacturing systems, producing the final factual cladogram. Evolutionary relationships between 53 candidate manufacturing systems, using 13 characters with 84 states, are hypothesised and presented diagrammatically. The manufacturing systems are also organised in a hierarchical classification with 13 genera, 6 families and 3 orders under one class of discrete manufacturing. Findings - This work addressed several weaknesses of current manufacturing cladistic classifications which include the lack of an explicit out-group comparison, limited conceptual cladogram development, limited use of characters and that previous classifications are specific to sectors. In order to correct these limitations, the paper first expands on previous work by producing a more generic manufacturing system classification. Second, it describes a novel web-based expert system for the practical application of the discrete manufacturing system. Practical implications - The classifications form the basis for a practical web-based expert system and diagnostic benchmarking tool, but also have a novel use in an educational context as it simplifies and relationally organises extant manufacturing system knowledge. Originality/value - The research employed a novel re-iterative methodology for both theory building, using observational data, producing the conceptual classification, and through theory testing developing the final factual cladogram that forms the basis for the practical web-based expert system and diagnostic tool.
| Language | English |
|---|---|
| Pages | 655-685 |
| Number of pages | 31 |
| Journal | Journal of Manufacturing Technology Management |
| Volume | 28 |
| Issue number | 5 |
| Early online date | 5 Jun 2017 |
| DOIs | |
| Publication status | E-pub ahead of print - 5 Jun 2017 |
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Keywords
- change management
- cladistic classification
- discrete manufacturing
- evolution
- knowledge-based systems
- linnaean classification
- manufacturing cladistics
- manufacturing development and change
- manufacturing systems
- organizational development
- organizational systematics
Cite this
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Manufacturing systematics and cladistics : state of the art and generic classification. / Rose-Anderssen, Christen; Baldwin, James; Ridgway, Keith.
In: Journal of Manufacturing Technology Management, Vol. 28, No. 5, 05.06.2017, p. 655-685.Research output: Contribution to journal › Article
TY - JOUR
T1 - Manufacturing systematics and cladistics
T2 - Journal of Manufacturing Technology Management
AU - Rose-Anderssen, Christen
AU - Baldwin, James
AU - Ridgway, Keith
PY - 2017/6/5
Y1 - 2017/6/5
N2 - Purpose - The purpose of this paper is to critically evaluate the state of the art of applications of organisational systematics and manufacturing cladistics in terms of strengths and weaknesses and introduce new generic cladistic and hierarchical classifications of discrete manufacturing systems. These classifications are the basis for a practical web-based expert system and diagnostic benchmarking tool. Design/methodology/approach - There were two stages for the research methods, with eight re-iterative steps: one for theory building, using secondary and observational data, producing conceptual classifications; the second stage for theory testing and theory development, using quantitative data from 153 companies and 510 manufacturing systems, producing the final factual cladogram. Evolutionary relationships between 53 candidate manufacturing systems, using 13 characters with 84 states, are hypothesised and presented diagrammatically. The manufacturing systems are also organised in a hierarchical classification with 13 genera, 6 families and 3 orders under one class of discrete manufacturing. Findings - This work addressed several weaknesses of current manufacturing cladistic classifications which include the lack of an explicit out-group comparison, limited conceptual cladogram development, limited use of characters and that previous classifications are specific to sectors. In order to correct these limitations, the paper first expands on previous work by producing a more generic manufacturing system classification. Second, it describes a novel web-based expert system for the practical application of the discrete manufacturing system. Practical implications - The classifications form the basis for a practical web-based expert system and diagnostic benchmarking tool, but also have a novel use in an educational context as it simplifies and relationally organises extant manufacturing system knowledge. Originality/value - The research employed a novel re-iterative methodology for both theory building, using observational data, producing the conceptual classification, and through theory testing developing the final factual cladogram that forms the basis for the practical web-based expert system and diagnostic tool.
AB - Purpose - The purpose of this paper is to critically evaluate the state of the art of applications of organisational systematics and manufacturing cladistics in terms of strengths and weaknesses and introduce new generic cladistic and hierarchical classifications of discrete manufacturing systems. These classifications are the basis for a practical web-based expert system and diagnostic benchmarking tool. Design/methodology/approach - There were two stages for the research methods, with eight re-iterative steps: one for theory building, using secondary and observational data, producing conceptual classifications; the second stage for theory testing and theory development, using quantitative data from 153 companies and 510 manufacturing systems, producing the final factual cladogram. Evolutionary relationships between 53 candidate manufacturing systems, using 13 characters with 84 states, are hypothesised and presented diagrammatically. The manufacturing systems are also organised in a hierarchical classification with 13 genera, 6 families and 3 orders under one class of discrete manufacturing. Findings - This work addressed several weaknesses of current manufacturing cladistic classifications which include the lack of an explicit out-group comparison, limited conceptual cladogram development, limited use of characters and that previous classifications are specific to sectors. In order to correct these limitations, the paper first expands on previous work by producing a more generic manufacturing system classification. Second, it describes a novel web-based expert system for the practical application of the discrete manufacturing system. Practical implications - The classifications form the basis for a practical web-based expert system and diagnostic benchmarking tool, but also have a novel use in an educational context as it simplifies and relationally organises extant manufacturing system knowledge. Originality/value - The research employed a novel re-iterative methodology for both theory building, using observational data, producing the conceptual classification, and through theory testing developing the final factual cladogram that forms the basis for the practical web-based expert system and diagnostic tool.
KW - change management
KW - cladistic classification
KW - discrete manufacturing
KW - evolution
KW - knowledge-based systems
KW - linnaean classification
KW - manufacturing cladistics
KW - manufacturing development and change
KW - manufacturing systems
KW - organizational development
KW - organizational systematics
UR - http://www.scopus.com/inward/record.url?scp=85026309829&partnerID=8YFLogxK
UR - https://www.emeraldinsight.com/loi/jmtm
UR - http://eprints.whiterose.ac.uk/118563/
U2 - 10.1108/JMTM-08-2016-0115
DO - 10.1108/JMTM-08-2016-0115
M3 - Article
VL - 28
SP - 655
EP - 685
JO - Journal of Manufacturing Technology Management
JF - Journal of Manufacturing Technology Management
SN - 1741-038X
IS - 5
ER -